Ignite Creation Date:
2025-12-24 @ 5:34 PM
Ignite Modification Date:
2025-12-25 @ 3:06 PM
Study NCT ID:
NCT07136168
Status:
RECRUITING
Last Update Posted:
2025-10-07
First Post:
2025-08-14
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Healthy Older Adults Through Movement and Engagement
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000073496', 'term': 'Frailty'}], 'ancestors': [{'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Randomization of the selected population 1:2 to intervention ( health dialogue) or care as usual. Single site.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 2952}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-08-25', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-08', 'completionDateStruct': {'date': '2031-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-10-01', 'studyFirstSubmitDate': '2025-08-14', 'studyFirstSubmitQcDate': '2025-08-21', 'lastUpdatePostDateStruct': {'date': '2025-10-07', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-08-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-03-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Change in health-related quality of life', 'timeFrame': 'Baseline, at 16 months and 6 years from start of intervention', 'description': 'EQ5D-5L (Euroqol 5 dimensions 5 levels) collected via postal questionnaire'}, {'measure': 'Change in quality of life', 'timeFrame': 'Baseline, at 16 months and at 6 years from study start', 'description': 'Quality of life measured by ICECAP-0 ( ICEpop CAPability measure for older people)'}], 'secondaryOutcomes': [{'measure': 'Hospital care days', 'timeFrame': '16 months, 3 years and 6 years', 'description': 'the total number of days that a participant is admitted to hospital'}, {'measure': 'Hospital care episodes', 'timeFrame': '16 months, 3 years and 6 years', 'description': 'The number of events a patient is admitted to hospital regardless of length of stay'}, {'measure': 'Healthcare visits', 'timeFrame': '16 months, 3 years and 6 years from start of intervention', 'description': 'The number of out-patient visits to physician or other healthcare profession in primary or secondary care'}, {'measure': 'Social care use', 'timeFrame': '16 months and 6 years from the start of the intervention', 'description': 'Number and type of services delivered from the municipality'}, {'measure': 'Mortality', 'timeFrame': '16 months, 3 years and 6 years from start of intervention', 'description': 'All-cause mortality'}, {'measure': 'Healthcare cost', 'timeFrame': '16 months, 3 years and 6 years from start of intervention', 'description': 'Total healthcare cost including primary, secondary out-patient care, community care and hospital care'}, {'measure': 'Cost-effectiveness', 'timeFrame': '16 months and 6 years from start of intervention', 'description': 'Incremental cost-effectiveness ratio (ICER) calculated by QALYs and YSC (Years of sufficient capability)'}, {'measure': 'Change in ADL (Activities of daily living)', 'timeFrame': 'at baseline, 16 months and 6 years from start of intervention', 'description': 'Activities of daily living measured by the ADL-staircase. 9 activities ( 5 Personal and 4 instrumental ADLs.'}, {'measure': 'Frailty', 'timeFrame': 'Baseline, at 16 months and 6 years from start of intervention', 'description': 'Self-reported frailty criteria derived from Frieds frailty phenotype. Five criteria, reporting of 2 crietria indicates pre-frailty and 3 criteria or more indicates frailty,'}, {'measure': 'Time to nursing home admission', 'timeFrame': '16 months and 6 years from start of intervention', 'description': 'Number of days/months that a participant stays in independent living from study start to nursing home admission'}, {'measure': 'Medication', 'timeFrame': '16 months and 6 years from start of intervention', 'description': 'Number and type of prescribed drugs'}, {'measure': 'Maintenance of own housing', 'timeFrame': 'At 16 months, at 3 years and 6 years from start of intervention', 'description': 'Number of days living in independent housing from study start to admission to nursing home'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['health dialogue', 'frailty', 'cost-effectiveness', 'ageing well', 'primary care', 'health related quality of life'], 'conditions': ['Frailty', 'Ageing Well', 'Prevention Intervention', 'Health Related Quality of Life']}, 'referencesModule': {'references': [{'pmid': '30666550', 'type': 'BACKGROUND', 'citation': 'Proud L, McLoughlin C, Kinghorn P. ICECAP-O, the current state of play: a systematic review of studies reporting the psychometric properties and use of the instrument over the decade since its publication. Qual Life Res. 2019 Jun;28(6):1429-1439. doi: 10.1007/s11136-019-02114-y. Epub 2019 Jan 21.'}, {'pmid': '30849098', 'type': 'BACKGROUND', 'citation': 'van Leeuwen KM, van Loon MS, van Nes FA, Bosmans JE, de Vet HCW, Ket JCF, Widdershoven GAM, Ostelo RWJG. What does quality of life mean to older adults? A thematic synthesis. PLoS One. 2019 Mar 8;14(3):e0213263. doi: 10.1371/journal.pone.0213263. eCollection 2019.'}, {'pmid': '29324562', 'type': 'BACKGROUND', 'citation': "Apostolo J, Cooke R, Bobrowicz-Campos E, Santana S, Marcucci M, Cano A, Vollenbroek-Hutten M, Germini F, D'Avanzo B, Gwyther H, Holland C. Effectiveness of interventions to prevent pre-frailty and frailty progression in older adults: a systematic review. JBI Database System Rev Implement Rep. 2018 Jan;16(1):140-232. doi: 10.11124/JBISRIR-2017-003382."}, {'pmid': '37924210', 'type': 'BACKGROUND', 'citation': 'Lincke A, Fagerstrom C, Ekstedt M, Lowe W, Backaberg S. A comparative study of the 2D- and 3D-based skeleton avatar technology for assessing physical activity and functioning among healthy older adults. Health Informatics J. 2023 Oct-Dec;29(4):14604582231214589. doi: 10.1177/14604582231214589.'}, {'pmid': '36149932', 'type': 'BACKGROUND', 'citation': 'Klunder JH, Panneman SL, Wallace E, de Vries R, Joling KJ, Maarsingh OR, van Hout HPJ. Prediction models for the prediction of unplanned hospital admissions in community-dwelling older adults: A systematic review. PLoS One. 2022 Sep 23;17(9):e0275116. doi: 10.1371/journal.pone.0275116. eCollection 2022.'}, {'pmid': '34322601', 'type': 'BACKGROUND', 'citation': 'Girwar SM, Jabroer R, Fiocco M, Sutch SP, Numans ME, Bruijnzeels MA. A systematic review of risk stratification tools internationally used in primary care settings. Health Sci Rep. 2021 Jul 23;4(3):e329. doi: 10.1002/hsr2.329. eCollection 2021 Sep.'}, {'pmid': '26190370', 'type': 'BACKGROUND', 'citation': 'Bender AM, Jorgensen T, Pisinger C. Is self-selection the main driver of positive interpretations of general health checks? The Inter99 randomized trial. Prev Med. 2015 Dec;81:42-8. doi: 10.1016/j.ypmed.2015.07.004. Epub 2015 Jul 17.'}, {'pmid': '32525878', 'type': 'BACKGROUND', 'citation': 'Nordstrom A, Bergman J, Bjork S, Carlberg B, Johansson J, Hult A, Nordstrom P. A multiple risk factor program is associated with decreased risk of cardiovascular disease in 70-year-olds: A cohort study from Sweden. PLoS Med. 2020 Jun 11;17(6):e1003135. doi: 10.1371/journal.pmed.1003135. eCollection 2020 Jun.'}, {'pmid': '30699470', 'type': 'BACKGROUND', 'citation': 'Krogsboll LT, Jorgensen KJ, Gotzsche PC. General health checks in adults for reducing morbidity and mortality from disease. Cochrane Database Syst Rev. 2019 Jan 31;1(1):CD009009. doi: 10.1002/14651858.CD009009.pub3.'}, {'pmid': '23245606', 'type': 'BACKGROUND', 'citation': 'Salomon JA, Wang H, Freeman MK, Vos T, Flaxman AD, Lopez AD, Murray CJ. Healthy life expectancy for 187 countries, 1990-2010: a systematic analysis for the Global Burden Disease Study 2010. Lancet. 2012 Dec 15;380(9859):2144-62. doi: 10.1016/S0140-6736(12)61690-0.'}]}, 'descriptionModule': {'briefSummary': "The HOME Project evaluates the effects of structured health dialogues with individuals aged 67-84 years in the municipality of Borgholm, Sweden. A combination of registry data and survey responses will be used to monitor quality of life, morbidity, healthcare needs, and lifestyle factors over a six-year period. Outcomes will be compared between randomized groups within Borgholm municipality and a matched control group from seven other municipalities in Region Kalmar.\n\nThe project also includes an analysis of cost-effectiveness and the reach of the intervention. A qualitative interview study will explore participants' perceptions of their health, their motivations for health improvement, and their experiences of how the health dialogues may influence these aspects.\n\nIn a substudy, machine learning models will be developed to predict functional decline and high healthcare needs among older adults. These models will be validated against established risk assessment tools such as the Adjusted Clinical Groups (ACG) system and the Charlson Comorbidity Index. Digital motion analysis using Skeleton Avatar Technology will be employed both independently and in combination with other variables to support model development.", 'detailedDescription': 'BACKGROUND: The world faces a demographic shift with an aging population and increasing numbers of older adults experiencing frailty and complex care needs. Effective preventive strategies are requested from many stakeholders . Health dialogues have been introduced in several Swedish regions to promote healthier aging, yet evidence for their effectiveness and cost-efficiency remains limited. While systematic reviews have not confirmed significant effects on morbidity or mortality, some cohort studies suggest benefits in cardiovascular outcomes and a few primary preventive interventions have been directed at older individuals. The results are disputed, and several authors argue that health dialogues and health checks tend to reach individuals with lower cardiovascular risk rather than those at highest risk \\[4\\]. There is a lack of studies linking the outcomes of health dialogues to different risk levels.\n\nOne strategy to identify individuals in the population at highest risk of morbidity is to use risk assessment instruments. In primary care populations, Adjusted Clinical Groups (ACG) and Charlson Comorbidity Index (CCI) are the most studied. In recent years, several predictive instruments/models using existing health and medical data have been developed to identify older individuals at risk of future functional decline and morbidity. However, the relatively moderate precision of these instruments limits their clinical usefulness. Digital motion analysis using the SAT (Skeleton Avatar Technology) technique has shown potential in assessing physical activity levels, mobility, and balance in older individuals. Still, data from broader populations of older individuals with a wide range of diseases and functional levels are lacking, and the method has not been tested for its predictive ability regarding functional decline and extensive care needs.\n\nAmong older individuals, the wide variation in health and functional levels creates a greater need for individualized advice and interventions. Holistic interventions targeting frail older individuals are well-studied, and there is some evidence of positive effects, although results are also conflicting. International recommendations point to a multifactorial causal relationship behind frailty/functional decline, and there is consensus that increased physical activity and reduced malnutrition can counteract these issues, and that an active lifestyle is associated with a reduced risk of frailty.\n\nA current question is which health outcomes are most important for the older population. Studies show that many older individuals value good quality of life and high independence more than maximum lifespan. As a complement to traditional measurements of health-related quality of life using EQ-5D, which focuses on symptoms and function, it is proposed to measure "Capability": the ability to perform activities that are meaningful and important to the individual . ICECAP-O is a quality-of-life instrument that has also been used for health economic evaluations \\[9\\].\n\nAIM:\n\nWe will evaluate the short - and long term effects of preventive health dialogues for older individuals. The project also aims to evaluate and further develop models to predict the risk of future illness. We will also examine which residents choose to participate and how participation affects both self-rated health and quality of life, as well as health and social care needs. This is important from an equity perspective: can health dialogues help reduce health disparities, or is there a risk that they reinforce existing inequalities in health between groups? For the same reason, we are conducting a cost-effectiveness analysis of health dialogues in an older population, examining the balance between cost and benefit.\n\nThe qualitative part of the project aims to increase understanding of what happens in the communication during health dialogues and what older individuals themselves perceive as influencing their motivation to take personal responsibility for their health.\n\nResearch questions:\n\n1. How does quality of life develop in the intervention group offered health dialogues compared to a) a randomized control group in the same municipality and b) a matched control group in a neighboring county?\n2. How do function, activity, and use of health and social care services develop in these groups?\n3. Is the health dialogue intervention cost-effective?\n4. Are there differences in risk levels and health outcomes between participants in health dialogues and those who choose not to participate?\n5. Is the effect of health dialogues influenced by the participant\'s risk level for morbidity and adverse health outcomes?\n6. Can digital motion analysis be used to predict the risk of future morbidity and functional decline?\n7. What do participants describe as influencing and motivating them to improve their health, and how do they reason about the priorities they make regarding their health? The primary outcome measure is quality of life, assessed using two complementary methods: EQ-5D and ICECAP-O. We include a broad age range of participants from early retirement age and upwards to gain more knowledge about which groups have the greatest need for and benefit from health dialogues.\n\n \\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\n\n Hypotheses:\n * Health dialogues should be targeted at specific risk groups within the older population to be cost-effective.\n * Digital motion analysis using Skeleton Avatar Technology (SAT) can be used alone or in combination with other variables to identify older individuals at high risk of developing functional decline and extensive care needs.\n\n STUDY DESIGN This is a mixed-methods study combining quantitative and qualitative approaches.The quantitative component includes a controlled intervention study with three groups: intervention, randomized control, and matched control. The qualitative component explores participants\' experiences and perceptions through interviews and thematic analysis.\n\n DATA COLLECTION Outcomes 1,2,11 and 12 will be collected by a postal/web-based questionnaire. All other outcomes will be collected from healthcare registries.\n\n ANALYSIS\n\n Effects of Health Dialogues:\n\n The following comparative analyses will be conducted:\n\n A: Differences between the intervention arm and the passive control arm (overall and stratified by risk level).\n\n B: Differences between the two randomized arms and the matched controls (overall and stratified by risk level).\n\n C: Differences between participants and non-participants within the intervention arm (overall and stratified by risk level).\n\n Differences in primary outcomes between intervention and control groups will be estimated using 95% confidence intervals. Appropriate statistical methods will be applied based on the type of outcome measure. Subgroup estimates will be calculated similarly, and relevant statistical tests for heterogeneity will be used. Risk stratification will be based on Adjusted Clinical Groups (ACG), Charlson Comorbidity Index (CCI), frailty status, and a predictive model for hospital admissions.\n\n The aim of these analyses is to obtain unbiased estimates of statistically significant differences in outcomes between groups. Given the randomized design, statistically significant differences will be interpreted as effects of the intervention. Analyses will follow the intention-to-treat (ITT) principle, which maintains group assignment throughout the study and is appropriate for this design.\n\n Cost-Effectiveness Analysis:\n\n The cost-effectiveness evaluation will estimate the total costs of the intervention using established health economic methods. The analysis will adopt a societal perspective. Costs will be compared to selected outcome measures and benchmarked against alternative resource use scenarios, such as no health dialogue or other similar interventions.\n\n Development of Risk Prediction Models:\n\n A combination of variables from electronic health records (diagnoses, healthcare contacts), surveys (self-rated health, symptoms, lifestyle factors), and digital motion analysis (SAT) will be collected. Machine learning models will be trained on these data to predict functional decline (ADL limitations and care needs) and morbidity (hospitalizations, healthcare visits, mortality). Techniques such as logistic regression, random forest, and neural networks will be used to optimize prediction accuracy. Model performance will be evaluated using AUC/ROC (Receiver Operating Characteristic Curve) and MAE (Mean Absolute Error).\n\n Motivational Factors in Health Dialogues:\n\n The qualitative sub-study aims to explore whether and how health dialogues influence motivation for adopting health-promoting behaviors. Interviews will focus on changes in participants\' views on personal responsibility for health, lifestyle choices, and behavioral change. Data will be analyzed using qualitative content analysis, without predefined categories or themes.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['OLDER_ADULT'], 'maximumAge': '84 Years', 'minimumAge': '67 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Living in Borgholm municipality or in one of 7 matched Demographical Statistical Area in Kalmar county\n* Age between 67-84 years\n\nExclusion Criteria:\n\n* Living in a nursing home\n* Not speaking or understanding swedish language'}, 'identificationModule': {'nctId': 'NCT07136168', 'acronym': 'HOME', 'briefTitle': 'Healthy Older Adults Through Movement and Engagement', 'organization': {'class': 'OTHER_GOV', 'fullName': 'Linkoeping University'}, 'officialTitle': 'Healthy Ageing - an Interdisciplinary Randomised Study of Health Dialogues in Primary Care', 'orgStudyIdInfo': {'id': '2024-04137-01'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Health dialogue', 'description': 'Participants will be invited to a health dialogue at primary health care center and to answer a questionnaire covering different aspects of health. Data from medical registers will be collected.', 'interventionNames': ['Behavioral: Health dialogue']}, {'type': 'NO_INTERVENTION', 'label': 'Passive control', 'description': 'Participant will be invited to answer a questionnaire covering different aspects of health. Data from medical registers will be collected.'}], 'interventions': [{'name': 'Health dialogue', 'type': 'BEHAVIORAL', 'description': '1. Pre-visit 20 minutes including timed-up and go (TUG) walking test, length, weight, blood pressure, and blood tests ( HbA1C, PEth)\n2. Structured health dialogue by a dedicated nurse practitioner for about 60 minutes covering living conditions, activity, everyday function, lifestyle habits and formation of a plan for improved health and referral to physician, physiotherapist or other primary care worker when appropriate\n3. Follow-up call at 3 months with the nurse practitioner for evaluation and adjustment of the plan', 'armGroupLabels': ['Health dialogue']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'SE - 58216', 'city': 'Borgholm', 'state': 'County of Kalmar', 'status': 'RECRUITING', 'country': 'Sweden', 'contacts': [{'name': 'Magnus Nord, PhD', 'role': 'CONTACT', 'email': 'magnus.nord@liu.se', 'phone': '+46-709631704'}], 'facility': 'Hälsocentralen i Borgholm', 'geoPoint': {'lat': 56.8793, 'lon': 16.65634}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED', 'description': 'Data may be made available upon request when the study is completed following the laws for sharing patient data'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Linkoeping University', 'class': 'OTHER_GOV'}, 'collaborators': [{'name': 'Linnaeus University', 'class': 'OTHER'}, {'name': 'Department of Clinical Sciences, Malmö. Faculty of Medicine, Lund University.', 'class': 'UNKNOWN'}, {'name': 'Göteborg University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'MD, PhD; Adjunct senior lecturer', 'investigatorFullName': 'Magnus Nord', 'investigatorAffiliation': 'Linkoeping University'}}}}